richard-moulton/d-stream

Implementation of the D-Stream clustering algorithm for use in MOA. An earlier version is included as part of the MOA 17.06 release.

D-Stream

Implementation of the D-Stream clustering algorithm for use in MOA. An earlier version is included as part of the MOA 17.06 release. A user-provided parameter to specify the grid width for numeric attributes has been added.

The D-Stream algorithm is described by Yixin Chen and Li Tu in their paper "Density-Based Clustering for Real-Time Stream Data" [2]. Please cite that paper if you use this code.

MOA (Massive Online Analysis) [1] is a Java-based, open source framework for data stream mining. More details can be found on its website and it can be found on GitHub as well (https://github.com/waikato/moa).

This project has a DOI:

REFERENCES

[1] A. Bifet, G. Holmes, R. Kirkby, and B. Pfahringer, “Moa: Massive online analysis,” J. Mach. Learn. Res., vol. 11, no. May, pp. 1601–1604, 2010.

[2] Y. Chen and L. Tu, “Density-Based Clustering for Real-Time Stream Data,” in Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, 2007, pp. 133–142. DOI: 10.1145/1281192.1281210